Literature DB >> 12123491

A comparison of combinatorial partitioning and linear regression for the detection of epistatic effects of the ACE I/D and PAI-1 4G/5G polymorphisms on plasma PAI-1 levels.

J H Moore1, J M Lamb, N J Brown, D E Vaughan.   

Abstract

The detection and characterization of epistasis or non-additive gene-gene interactions remains a statistical challenge in genetic epidemiology. The recently developed combinatorial partitioning method (CPM) may overcome some of the limitations of linear regression for the exploratory analysis of non-additive epistatic effects. The goal of this study was to compare CPM with linear regression analysis for the exploratory analysis of non-additive interactive effects of the angiotensin converting enzyme (ACE) insertion/deletion (I/D) and plasminogen activator inhibitor 1 (PAI-1) 4G/5G polymorphisms on plasma PAI-1 levels in a sample of 50 unrelated African Americans and 117 unrelated Caucasians. Using linear regression, we documented the additive effects of the ACE and PAI-1 genes on plasma PAI-1 levels in African American females (R(2) = 0.10), African American males (R(2) = 0.16), Caucasian females (R(2) = 0.11), and Caucasian males (R2 = 0.09). Using CPM, we found evidence for non-additive effects of the ACE and PAI-1 genes in both African American females (R(2) = 0.22) and African American males (R(2) = 0.24) but not in Caucasian females (R(2) = 0.10) or Caucasian males (R(2) = 0.11). The results of this exploratory data analysis support previous experimental, clinical, and epidemiological studies that have proposed as a working hypothesis that the ACE gene mediates interaction effects of the fibrinolytic and renin-angiotensin systems on plasma levels of PAI-1.

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Year:  2002        PMID: 12123491     DOI: 10.1034/j.1399-0004.2002.620110.x

Source DB:  PubMed          Journal:  Clin Genet        ISSN: 0009-9163            Impact factor:   4.438


  8 in total

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2.  Analysis of gene-gene interactions.

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4.  The effects of polymorphisms in genes from the renin-angiotensin, bradykinin, and fibrinolytic systems on plasma t-PA and PAI-1 levels are dependent on environmental context.

Authors:  Folkert W Asselbergs; Scott M Williams; Patricia R Hebert; Christopher S Coffey; Hans L Hillege; Harold Snieder; Gerjan Navis; Douglas E Vaughan; Wiek H van Gilst; Jason H Moore
Journal:  Hum Genet       Date:  2007-06-26       Impact factor: 4.132

5.  The challenge for genetic epidemiologists: how to analyze large numbers of SNPs in relation to complex diseases.

Authors:  A Geert Heidema; Jolanda M A Boer; Nico Nagelkerke; Edwin C M Mariman; Daphne L van der A; Edith J M Feskens
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7.  Neural network analysis in pharmacogenetics of mood disorders.

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Journal:  BMC Med Genet       Date:  2004-12-09       Impact factor: 2.103

8.  An application of conditional logistic regression and multifactor dimensionality reduction for detecting gene-gene interactions on risk of myocardial infarction: the importance of model validation.

Authors:  Christopher S Coffey; Patricia R Hebert; Marylyn D Ritchie; Harlan M Krumholz; J Michael Gaziano; Paul M Ridker; Nancy J Brown; Douglas E Vaughan; Jason H Moore
Journal:  BMC Bioinformatics       Date:  2004-04-30       Impact factor: 3.169

  8 in total

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